Abstract
The advance of all forms of digital and virtual heritage alongside numerous heritage science and management applications have led to the generation of growing amounts of heritage data. This data is increasingly rich, diverse and powerful. To get the most out of heritage data, there is an evident need to effectively understand, manage and exploit it in a way that is sensitive towards its context, responding to its singularities, and that can allow heritage to keep up with global changes regarding expansion of digital technologies and the increasing role of data in decision making and policy development. Through conversations with industry and academia, as well as through their personal research in the field of cultural heritage, the authors have identified a need for enhanced training for data scientists to prepare them for working in the heritage sector. This paper first proposes a definition of the term heritage data, so far missing from the literature, and then presents the academic rationale behind the identified need for targeted training in data science for cultural heritage.
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We are grateful to all interviewees and questionnaire respondents for their generous collaboration and to Yujia Luo for her help with Mendeley.
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Albuerne, A., Grau-Bove, J., Strlic, M. (2018). The Role of Heritage Data Science in Digital Heritage. In: Ioannides, M., et al. Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2018. Lecture Notes in Computer Science(), vol 11196. Springer, Cham. https://doi.org/10.1007/978-3-030-01762-0_54
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DOI: https://doi.org/10.1007/978-3-030-01762-0_54
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